So, in my earlier post, I said I had a “convergent mnist network”. At the time I was excited and I wrote that in haste. What that network had been doing, it had been trained on null and digits, but only one image for each of these digit was actually ever trained into the network.Continue reading “Errors and Progress in mnist recognition”
Tag Archives: Ai
Configurations of random variables
In my neural network program, I refactored some code and produced an error which I did not notice for some time. When I would run the program, eventually, out of 100 networks, a single or few networks would learn the pathing problem. With no difference in how they are trained, they are all taught exactlyContinue reading “Configurations of random variables”
Dumb Neural Networks
Lottery Ticket Theory says that some networks do not train well if at all, based on random properties of the network. In my current project, I have 100 agents, each with their own neural network, same shape. Each of these networks trains exactly the same way, but some end up acting smart and others dumb.Continue reading “Dumb Neural Networks”
Lottery Ticket Hypothesis in action
I have written an application which creates pools of 1000 neural networks. One test performs backpropagation training on them. A second test performs backpropagation, and a genetic algorithm. The amount of times training is called for each test is the same. The genetic algorithm seems to actually be able to converge on a lottery ticketContinue reading “Lottery Ticket Hypothesis in action”
My AI study so far
I have been studying neural networks for some time, and recently during a YSU hackthon, I managed to make interesting progress. After about a year long break, I return to this code and make large amounts of progress and a number of topics have presented in C++ software. I’m going to describe some of myContinue reading “My AI study so far”